A Library which provides more information about suitable Machine learning algorithm for your dataset

Project description

Model Selection

As a beginner in Data science/Machine learning field, most of us having issue in Feature Selection, Feature Extraction and Model Selection. Algorithm-Finder can help you to solve this problem. using Algorithm-Finder you can achieve the below tasks and more.
- Model Selection
- Feature Selection
- Feature Extraction
- Optimized tuning parameters
This package mainly used scikit-learn for most of the estimators, by using Algorithm-Finder you can apply your dataset on below models
- ALL --> ALL IN
- MLR --> MultiLinearRegression
- POLY --> PolynomialRegression
- SVR --> SupportVectorRegression
- DTREE --> DecisionTreeRegression & DecisionTreeClassification
- RFR --> RandomForestRegression
- SIGMOID --> LogisticRegression
- KNN --> K-NearestNeighbours Classifier
- SVM --> SupportVectorMachine Classifier
- RFC --> RandomForestClassifier
- BAYESIAN --> NaiveBayesClassifier

This version

0.0.1

Dec 15, 2019

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